AI-Driven Humanoidoid Personnel Acquisition: Is A Game Changer
Dhanalakshmi Mohanasundaram
LEAD College of Management
University of Calicut, Palakkad, Kerala, India
dlakshmi.shan@gmail.com
https://orchid.org/0009-0001-6095-1874
Abstract
The amalgamation of Artificial Intelligence in Personnel acquisition has reformed how concerns mesmerize, screen, and hire intrants. Artificial Intelligence-driven tools and podiums can streamline the acquisition process, reduce preconceptions, and improve the overall intranet experience. In today’s modest era, industries and institutions require excellent personnel to accomplish their ideas. This requirement is even more marked as the fourth industrial revolution (4.0) arrives. Organizations must find optimistic, budding, and energetic personnel to endure rivalry in this digital ecosphere. An effective personnel acquisition stratagem is crucial for hiring appropriate personalities who can succeed in the digital landscape and embryonic business milieu. A stylish strategy is vital for any organization. It helps in recognizing and hiring expert personnel who can competently and excellently accomplish job objectives. This strategy is a foremost function of an organization and progressively relies on data analysis to make informed decisions. This paper aims to explore how Artificial Intelligence influences strategies. It will also highlight the techniques companies use in Artificial intelligence-driven recruitment processes. The study depends utterly on secondary statistics sources, including conceptual papers, peer-reviewed journal articles, books, and websites, to further explore the concept of Artificial Intelligence as a game changer.
Keywords: Keywords: Artificial Intelligence, acquisition, conscription, humanoid, personnel
acquisition, preconceptions
How to Cite this Paper :
Dhanalakshmi, M. (2025). AI-Driven Humanoidoid Personnel Acquisition: Is A Game Changer. Atras Journal, 6 (1), 219-230.
DOI: https://doi.org/10.70091/Atras/vol06no01.15
References:
Allen, J. F. (1998). Artificial intelligence growing up: The changes and opportunities. Artificial Intelligence Magazine, 19(4), 13-13.
Arthur, J. (2001). Recruitment and selection. Journal of Human Resource Management, 15(2), 123-135.
Cleverism. (n.d.). Industry 4.0: Definition, Design Principles, Challenges, and the Future of Employment. https://www.cleverism.com/industry-4-0
Cowan, D. (1985). Artificial intelligence at Edinburgh University. Computer-Aided Design, 17(9), 465
Encyclopaedia Britannica. (2023, July 28). Artificial intelligence. In Encyclopaedia Britannica. Retrieved from https://www.britannica.com/technology/artificial-intelligence-469.
Finnigan, J. J. (1973). The right people in the right jobs. Business Books
Flippo, E. B. (1984). Personnel Management. McGraw-Hill
Florida, L. (2020). What the near future of artificial intelligence could be. In The 2019 Yearbook of the Digital Ethics Lab (pp. 127-142). Springer, Cham.
Ghosh, S., & Mitra, I. (2017). Message from PwC. In Mansfield, Wooster, & Marion (2016), Staffing decisions: Artificial intelligence and human resources.
Holm, A. (2010). The effect of e-recruitment on the recruitment process: Evidence from case studies of three Danish MNCs. In Proceedings of the 3rd European Academic Workshop on Electronic Human Resource Management (pp. 91-111).
Kestenbaum, B. (2023). The evolving role of artificial intelligence in HR operations. Talent Tech Insights.
Laurano, M. (2019). How AI is improving the candidate experience. LinkedIn Talent Blog.
Laurano, M. (2020). The impact of AI on recruitment. Aptitude Research.
Laurano, M. (2021). Talent acquisition technology 2021. Aptitude Research.
Louw, G. J. (2013). Exploring recruitment and selection trends in the Eastern Cape. SA Journal of Human Resource Management, 11(1). https://doi.org/10.4102/sajhrm.v11i1.319
McCarthy, J. (1959). Programs with common sense. In Mechanization of Thought Processes: Proceedings of the Symposium (pp. 184-195). Teddington, England: National Physical Laboratory.
McCarthy, J. (1960). Recursive functions of symbolic expressions and their computation by machine, part I. Communications of the ACM, 3(4), 184-195.
McCarthy, J. (2007). What is artificial intelligence? Retrieved from http://www-formal.stanford.edu/jmc/whatisai/whatisai.htm
McCarthy, J., Minsky, M., Rochester, N., & Shannon, C. (1956). A proposal for the Dartmouth summer research project on artificial intelligence. Dartmouth Conference, Hanover, NH.
McCarthy, J., Minsky, M., Rochester, N., & Shannon, C. E. (1956). A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence.
Mondy, R. W. (2010). Human resource management (11th ed.). Prentice Hall.
Muthukumaran, C. K. (2014). Recruitment process: A study among the employees at the information technology (IT) industry in Chennai. International Journal of Management Research and Reviews, 4(1), 91-100.
Rao, P. (2010). A resource‐based analysis of recruitment and selection practices of Indian software companies: A case study approach. Journal of Indian Business Research, 2 (1), 32-51.
Rawat, A. (2024). Applications of Artificial Intelligence in Science. International Journal of Pharmaceutical Science and Medicine, 2(2), 53-63. DOI: 10.70199/IJPSM.2.2.53-63.
Rich, E., & Knight, K. (1991). Artificial intelligence. McGraw-Hill.
Winfield, A. (2020). Intelligence is not one thing. Journal of Artificial General Intelligence, 11(2), 97-100.
Copyright for all articles published in ATRAS belongs to the author. The authors also grant permission to the publisher to publish, reproduce, distribute, and transmit the articles. ATRAS publishes accepted papers under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License. Authors submitting papers for publication in ATRAS agree to apply the CC BY-NC 4.0 license to their work. For non-commercial purposes, anyone may copy, redistribute material, remix, transform, and construct material in any media or format, provided that the terms of the license are observed and the original source is properly cited.